Overview

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In today’s fast-paced business environment, optimizing Power BI performance is essential to building scalable and efficient solutions. This course teaches data professionals practical techniques to enhance the speed and efficiency of Power BI reports, empowering them to meet demanding performance requirements. By diving deep into key topics such as data modeling, DAX, and performance management, this course will help learners overcome the common challenges of slow reports and poor data transformations. Learners will acquire actionable insights, equipping them to deliver high-speed, optimized Power BI solutions in their organizations. What sets this course apart is its blend of theory and real-world applications. Through a combination of technical explanations and illustrative examples, learners will get hands-on experience with the tools and practices required to improve Power BI performance, ensuring they can apply what they learn to actual business scenarios. This course is designed for data analysts, BI developers, and professionals who already have basic familiarity with Power BI. It is perfect for anyone looking to elevate their Power BI solutions and optimize performance, regardless of industry. Based on the book, Microsoft Power BI Performance Best Practices, by Thomas LeBlanc and Bhavik Merchant.

Syllabus

Setting Targets and Identifying Problem Areas

In this section, we define performance targets for Power BI solutions, analyze factors affecting report and data performance, and explore strategies for consistent management.

Exploring Power BI Architecture and Configuration

In this section, we examine Power BI architecture, focusing on data storage modes, gateway deployment, and log analysis to optimize performance and scalability for efficient data delivery.

Learning the Tools for Performance Tuning

In this section, we explore Power BI performance tools to analyze and optimize report efficiency, focusing on metrics and diagnostics for improved user experience.

Analyzing Logs and Metrics

In this section, we explore collecting and analyzing Power BI performance data using metrics, logs, and Azure monitoring tools to identify bottlenecks and optimize report efficiency.

Optimization for Storage Modes

In this section, we explore DirectQuery and DirectLake optimizations, focusing on reducing data source load and leveraging cloud capabilities for scalable performance in Power BI models.

Third-Party Utilities

In this section, we explore third-party utilities like Power BI Helper, Tabular Editor, and DAX Studio to analyze and optimize Power BI model performance and query efficiency.

Performance Governance Framework

In this section, we explore structured performance monitoring, root cause analysis, and repeatable improvement processes for Power BI to ensure sustainable BI solution efficiency.

Loading, Transforming, and Refreshing Data

In this section, we explore efficient data loading, transformation, and refresh strategies in Power BI to optimize performance and reduce resource usage.

Report and Dashboard Design

In this section, we explore optimizing report layouts, interaction patterns, and dashboard design to enhance performance and user experience in Power BI.

Dimensional Modeling and Row Level Security

In this section, we explore efficient Power BI semantic model design, focusing on single-source truth, performance optimization, and RLS implementation for reliable data delivery.

Improving DAX

In this section, we examine DAX performance optimization by analyzing row and filter context, improving calculated columns, and applying efficient design patterns for better query efficiency in Power BI.

High Scale Patterns

In this section, we explore strategies for managing large data volumes using composite models, aggregations, and Azure technologies like AAS and Fabric for scalable architectures.

Working with Capacities

In this section, we explore Power BI Premium and Fabric capacities, focusing on capacity planning, workload monitoring, and optimization strategies to ensure efficient resource use and performance in real-world deployments.

Performance Needs for Fabric Artifacts

In this section, we explore Fabric artifacts for data management, Direct Lake integration, and resource monitoring to enhance data warehouse efficiency and real-time analytics.

Embedding in Web Apps

In this section, we explore embedding Power BI content into web apps, focusing on optimizing performance and monitoring embedded reports using Fabric tools.